{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "from matplotlib import style\n",
    "\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'svg'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Preclose</th>\n",
       "      <th>Open</th>\n",
       "      <th>Highest</th>\n",
       "      <th>Lowest</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Money</th>\n",
       "      <th>Return</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Day</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1990-12-19</th>\n",
       "      <td>NaN</td>\n",
       "      <td>96.050</td>\n",
       "      <td>99.980</td>\n",
       "      <td>95.790</td>\n",
       "      <td>99.980</td>\n",
       "      <td>126000.00</td>\n",
       "      <td>4.940000e+05</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-12-20</th>\n",
       "      <td>99.980</td>\n",
       "      <td>104.300</td>\n",
       "      <td>104.390</td>\n",
       "      <td>99.980</td>\n",
       "      <td>104.390</td>\n",
       "      <td>19700.00</td>\n",
       "      <td>8.400000e+04</td>\n",
       "      <td>0.044109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-12-21</th>\n",
       "      <td>104.390</td>\n",
       "      <td>109.070</td>\n",
       "      <td>109.130</td>\n",
       "      <td>103.730</td>\n",
       "      <td>109.130</td>\n",
       "      <td>2800.00</td>\n",
       "      <td>1.600000e+04</td>\n",
       "      <td>0.045407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-12-24</th>\n",
       "      <td>109.130</td>\n",
       "      <td>113.570</td>\n",
       "      <td>114.550</td>\n",
       "      <td>109.130</td>\n",
       "      <td>114.550</td>\n",
       "      <td>3200.00</td>\n",
       "      <td>3.100000e+04</td>\n",
       "      <td>0.049666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-12-25</th>\n",
       "      <td>114.550</td>\n",
       "      <td>120.090</td>\n",
       "      <td>120.250</td>\n",
       "      <td>114.550</td>\n",
       "      <td>120.250</td>\n",
       "      <td>1500.00</td>\n",
       "      <td>6.000000e+03</td>\n",
       "      <td>0.049760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-24</th>\n",
       "      <td>2748.918</td>\n",
       "      <td>2770.754</td>\n",
       "      <td>2863.152</td>\n",
       "      <td>2761.372</td>\n",
       "      <td>2863.126</td>\n",
       "      <td>4776195.45</td>\n",
       "      <td>4.427953e+07</td>\n",
       "      <td>0.041547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-25</th>\n",
       "      <td>2863.126</td>\n",
       "      <td>2901.419</td>\n",
       "      <td>2952.451</td>\n",
       "      <td>2889.048</td>\n",
       "      <td>2896.306</td>\n",
       "      <td>5682598.16</td>\n",
       "      <td>5.166981e+07</td>\n",
       "      <td>0.011589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-26</th>\n",
       "      <td>2896.306</td>\n",
       "      <td>2893.745</td>\n",
       "      <td>3000.953</td>\n",
       "      <td>2889.014</td>\n",
       "      <td>3000.953</td>\n",
       "      <td>5763192.61</td>\n",
       "      <td>5.246691e+07</td>\n",
       "      <td>0.036131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-27</th>\n",
       "      <td>3000.953</td>\n",
       "      <td>3049.103</td>\n",
       "      <td>3087.529</td>\n",
       "      <td>3017.445</td>\n",
       "      <td>3087.529</td>\n",
       "      <td>4922871.63</td>\n",
       "      <td>4.806126e+07</td>\n",
       "      <td>0.028850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-30</th>\n",
       "      <td>3087.529</td>\n",
       "      <td>3194.722</td>\n",
       "      <td>3358.588</td>\n",
       "      <td>3153.697</td>\n",
       "      <td>3336.497</td>\n",
       "      <td>11023379.17</td>\n",
       "      <td>1.167773e+08</td>\n",
       "      <td>0.080637</td>\n",
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       "<p>8251 rows × 8 columns</p>\n",
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      ],
      "text/plain": [
       "            Preclose      Open   Highest    Lowest     Close       Volume  \\\n",
       "Day                                                                         \n",
       "1990-12-19       NaN    96.050    99.980    95.790    99.980    126000.00   \n",
       "1990-12-20    99.980   104.300   104.390    99.980   104.390     19700.00   \n",
       "1990-12-21   104.390   109.070   109.130   103.730   109.130      2800.00   \n",
       "1990-12-24   109.130   113.570   114.550   109.130   114.550      3200.00   \n",
       "1990-12-25   114.550   120.090   120.250   114.550   120.250      1500.00   \n",
       "...              ...       ...       ...       ...       ...          ...   \n",
       "2024-09-24  2748.918  2770.754  2863.152  2761.372  2863.126   4776195.45   \n",
       "2024-09-25  2863.126  2901.419  2952.451  2889.048  2896.306   5682598.16   \n",
       "2024-09-26  2896.306  2893.745  3000.953  2889.014  3000.953   5763192.61   \n",
       "2024-09-27  3000.953  3049.103  3087.529  3017.445  3087.529   4922871.63   \n",
       "2024-09-30  3087.529  3194.722  3358.588  3153.697  3336.497  11023379.17   \n",
       "\n",
       "                   Money    Return  \n",
       "Day                                 \n",
       "1990-12-19  4.940000e+05       NaN  \n",
       "1990-12-20  8.400000e+04  0.044109  \n",
       "1990-12-21  1.600000e+04  0.045407  \n",
       "1990-12-24  3.100000e+04  0.049666  \n",
       "1990-12-25  6.000000e+03  0.049760  \n",
       "...                  ...       ...  \n",
       "2024-09-24  4.427953e+07  0.041547  \n",
       "2024-09-25  5.166981e+07  0.011589  \n",
       "2024-09-26  5.246691e+07  0.036131  \n",
       "2024-09-27  4.806126e+07  0.028850  \n",
       "2024-09-30  1.167773e+08  0.080637  \n",
       "\n",
       "[8251 rows x 8 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('000001.csv')\n",
    "data['Day'] = pd.to_datetime(data['Day'], format='%Y/%m/%d')\n",
    "data.set_index('Day', inplace=True)\n",
    "data['Close'] = pd.to_numeric(data['Close'])\n",
    "data['Preclose'] = data['Close'].shift(1)\n",
    "data['Return'] = data['Close'] / data['Preclose'] - 1\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Return</th>\n",
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       "      <th>Day</th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1995-01-31</th>\n",
       "      <td>-0.131631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-02-28</th>\n",
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       "    <tr>\n",
       "      <th>1995-03-31</th>\n",
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       "      <th>1995-04-30</th>\n",
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       "    <tr>\n",
       "      <th>1995-05-31</th>\n",
       "      <td>0.207922</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <th>2024-05-31</th>\n",
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      "text/plain": [
       "              Return\n",
       "Day                 \n",
       "1995-01-31 -0.131631\n",
       "1995-02-28 -0.023694\n",
       "1995-03-31  0.177803\n",
       "1995-04-30 -0.103552\n",
       "1995-05-31  0.207922\n",
       "...              ...\n",
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       "2024-07-31 -0.009656\n",
       "2024-08-31 -0.032849\n",
       "2024-09-30  0.173908\n",
       "\n",
       "[357 rows x 1 columns]"
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     },
     "execution_count": 18,
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   "source": [
    "data_new = data['1995-01-01':'2024-12-31'].copy()\n",
    "Month_data = data_new.resample('M')['Return'].apply(lambda x: (1+x).prod()-1).to_frame()\n",
    "Month_data"
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  {
   "cell_type": "code",
   "execution_count": 19,
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   "source": [
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "ax.plot('Return', \n",
    "        '^-',\n",
    "        label='Monthly Return', \n",
    "        color='r',\n",
    "        linewidth=1,\n",
    "        data=Month_data['1995':'2024'])\n",
    "\n",
    "plt.show()"
   ]
  },
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     "text": [
      "Help on function plot in module matplotlib.pyplot:\n",
      "\n",
      "plot(*args, scalex=True, scaley=True, data=None, **kwargs)\n",
      "    Plot y versus x as lines and/or markers.\n",
      "    \n",
      "    Call signatures::\n",
      "    \n",
      "        plot([x], y, [fmt], *, data=None, **kwargs)\n",
      "        plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)\n",
      "    \n",
      "    The coordinates of the points or line nodes are given by *x*, *y*.\n",
      "    \n",
      "    The optional parameter *fmt* is a convenient way for defining basic\n",
      "    formatting like color, marker and linestyle. It's a shortcut string\n",
      "    notation described in the *Notes* section below.\n",
      "    \n",
      "    >>> plot(x, y)        # plot x and y using default line style and color\n",
      "    >>> plot(x, y, 'bo')  # plot x and y using blue circle markers\n",
      "    >>> plot(y)           # plot y using x as index array 0..N-1\n",
      "    >>> plot(y, 'r+')     # ditto, but with red plusses\n",
      "    \n",
      "    You can use `.Line2D` properties as keyword arguments for more\n",
      "    control on the appearance. Line properties and *fmt* can be mixed.\n",
      "    The following two calls yield identical results:\n",
      "    \n",
      "    >>> plot(x, y, 'go--', linewidth=2, markersize=12)\n",
      "    >>> plot(x, y, color='green', marker='o', linestyle='dashed',\n",
      "    ...      linewidth=2, markersize=12)\n",
      "    \n",
      "    When conflicting with *fmt*, keyword arguments take precedence.\n",
      "    \n",
      "    \n",
      "    **Plotting labelled data**\n",
      "    \n",
      "    There's a convenient way for plotting objects with labelled data (i.e.\n",
      "    data that can be accessed by index ``obj['y']``). Instead of giving\n",
      "    the data in *x* and *y*, you can provide the object in the *data*\n",
      "    parameter and just give the labels for *x* and *y*::\n",
      "    \n",
      "    >>> plot('xlabel', 'ylabel', data=obj)\n",
      "    \n",
      "    All indexable objects are supported. This could e.g. be a `dict`, a\n",
      "    `pandas.DataFrame` or a structured numpy array.\n",
      "    \n",
      "    \n",
      "    **Plotting multiple sets of data**\n",
      "    \n",
      "    There are various ways to plot multiple sets of data.\n",
      "    \n",
      "    - The most straight forward way is just to call `plot` multiple times.\n",
      "      Example:\n",
      "    \n",
      "      >>> plot(x1, y1, 'bo')\n",
      "      >>> plot(x2, y2, 'go')\n",
      "    \n",
      "    - If *x* and/or *y* are 2D arrays a separate data set will be drawn\n",
      "      for every column. If both *x* and *y* are 2D, they must have the\n",
      "      same shape. If only one of them is 2D with shape (N, m) the other\n",
      "      must have length N and will be used for every data set m.\n",
      "    \n",
      "      Example:\n",
      "    \n",
      "      >>> x = [1, 2, 3]\n",
      "      >>> y = np.array([[1, 2], [3, 4], [5, 6]])\n",
      "      >>> plot(x, y)\n",
      "    \n",
      "      is equivalent to:\n",
      "    \n",
      "      >>> for col in range(y.shape[1]):\n",
      "      ...     plot(x, y[:, col])\n",
      "    \n",
      "    - The third way is to specify multiple sets of *[x]*, *y*, *[fmt]*\n",
      "      groups::\n",
      "    \n",
      "      >>> plot(x1, y1, 'g^', x2, y2, 'g-')\n",
      "    \n",
      "      In this case, any additional keyword argument applies to all\n",
      "      datasets. Also this syntax cannot be combined with the *data*\n",
      "      parameter.\n",
      "    \n",
      "    By default, each line is assigned a different style specified by a\n",
      "    'style cycle'. The *fmt* and line property parameters are only\n",
      "    necessary if you want explicit deviations from these defaults.\n",
      "    Alternatively, you can also change the style cycle using\n",
      "    :rc:`axes.prop_cycle`.\n",
      "    \n",
      "    \n",
      "    Parameters\n",
      "    ----------\n",
      "    x, y : array-like or scalar\n",
      "        The horizontal / vertical coordinates of the data points.\n",
      "        *x* values are optional and default to ``range(len(y))``.\n",
      "    \n",
      "        Commonly, these parameters are 1D arrays.\n",
      "    \n",
      "        They can also be scalars, or two-dimensional (in that case, the\n",
      "        columns represent separate data sets).\n",
      "    \n",
      "        These arguments cannot be passed as keywords.\n",
      "    \n",
      "    fmt : str, optional\n",
      "        A format string, e.g. 'ro' for red circles. See the *Notes*\n",
      "        section for a full description of the format strings.\n",
      "    \n",
      "        Format strings are just an abbreviation for quickly setting\n",
      "        basic line properties. All of these and more can also be\n",
      "        controlled by keyword arguments.\n",
      "    \n",
      "        This argument cannot be passed as keyword.\n",
      "    \n",
      "    data : indexable object, optional\n",
      "        An object with labelled data. If given, provide the label names to\n",
      "        plot in *x* and *y*.\n",
      "    \n",
      "        .. note::\n",
      "            Technically there's a slight ambiguity in calls where the\n",
      "            second label is a valid *fmt*. ``plot('n', 'o', data=obj)``\n",
      "            could be ``plt(x, y)`` or ``plt(y, fmt)``. In such cases,\n",
      "            the former interpretation is chosen, but a warning is issued.\n",
      "            You may suppress the warning by adding an empty format string\n",
      "            ``plot('n', 'o', '', data=obj)``.\n",
      "    \n",
      "    Returns\n",
      "    -------\n",
      "    list of `.Line2D`\n",
      "        A list of lines representing the plotted data.\n",
      "    \n",
      "    Other Parameters\n",
      "    ----------------\n",
      "    scalex, scaley : bool, default: True\n",
      "        These parameters determine if the view limits are adapted to the\n",
      "        data limits. The values are passed on to `autoscale_view`.\n",
      "    \n",
      "    **kwargs : `.Line2D` properties, optional\n",
      "        *kwargs* are used to specify properties like a line label (for\n",
      "        auto legends), linewidth, antialiasing, marker face color.\n",
      "        Example::\n",
      "    \n",
      "        >>> plot([1, 2, 3], [1, 2, 3], 'go-', label='line 1', linewidth=2)\n",
      "        >>> plot([1, 2, 3], [1, 4, 9], 'rs', label='line 2')\n",
      "    \n",
      "        If you specify multiple lines with one plot call, the kwargs apply\n",
      "        to all those lines. In case the label object is iterable, each\n",
      "        element is used as labels for each set of data.\n",
      "    \n",
      "        Here is a list of available `.Line2D` properties:\n",
      "    \n",
      "        Properties:\n",
      "        agg_filter: a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array\n",
      "        alpha: scalar or None\n",
      "        animated: bool\n",
      "        antialiased or aa: bool\n",
      "        clip_box: `.Bbox`\n",
      "        clip_on: bool\n",
      "        clip_path: Patch or (Path, Transform) or None\n",
      "        color or c: color\n",
      "        dash_capstyle: `.CapStyle` or {'butt', 'projecting', 'round'}\n",
      "        dash_joinstyle: `.JoinStyle` or {'miter', 'round', 'bevel'}\n",
      "        dashes: sequence of floats (on/off ink in points) or (None, None)\n",
      "        data: (2, N) array or two 1D arrays\n",
      "        drawstyle or ds: {'default', 'steps', 'steps-pre', 'steps-mid', 'steps-post'}, default: 'default'\n",
      "        figure: `.Figure`\n",
      "        fillstyle: {'full', 'left', 'right', 'bottom', 'top', 'none'}\n",
      "        gid: str\n",
      "        in_layout: bool\n",
      "        label: object\n",
      "        linestyle or ls: {'-', '--', '-.', ':', '', (offset, on-off-seq), ...}\n",
      "        linewidth or lw: float\n",
      "        marker: marker style string, `~.path.Path` or `~.markers.MarkerStyle`\n",
      "        markeredgecolor or mec: color\n",
      "        markeredgewidth or mew: float\n",
      "        markerfacecolor or mfc: color\n",
      "        markerfacecoloralt or mfcalt: color\n",
      "        markersize or ms: float\n",
      "        markevery: None or int or (int, int) or slice or list[int] or float or (float, float) or list[bool]\n",
      "        path_effects: `.AbstractPathEffect`\n",
      "        picker: float or callable[[Artist, Event], tuple[bool, dict]]\n",
      "        pickradius: float\n",
      "        rasterized: bool\n",
      "        sketch_params: (scale: float, length: float, randomness: float)\n",
      "        snap: bool or None\n",
      "        solid_capstyle: `.CapStyle` or {'butt', 'projecting', 'round'}\n",
      "        solid_joinstyle: `.JoinStyle` or {'miter', 'round', 'bevel'}\n",
      "        transform: unknown\n",
      "        url: str\n",
      "        visible: bool\n",
      "        xdata: 1D array\n",
      "        ydata: 1D array\n",
      "        zorder: float\n",
      "    \n",
      "    See Also\n",
      "    --------\n",
      "    scatter : XY scatter plot with markers of varying size and/or color (\n",
      "        sometimes also called bubble chart).\n",
      "    \n",
      "    Notes\n",
      "    -----\n",
      "    **Format Strings**\n",
      "    \n",
      "    A format string consists of a part for color, marker and line::\n",
      "    \n",
      "        fmt = '[marker][line][color]'\n",
      "    \n",
      "    Each of them is optional. If not provided, the value from the style\n",
      "    cycle is used. Exception: If ``line`` is given, but no ``marker``,\n",
      "    the data will be a line without markers.\n",
      "    \n",
      "    Other combinations such as ``[color][marker][line]`` are also\n",
      "    supported, but note that their parsing may be ambiguous.\n",
      "    \n",
      "    **Markers**\n",
      "    \n",
      "    =============   ===============================\n",
      "    character       description\n",
      "    =============   ===============================\n",
      "    ``'.'``         point marker\n",
      "    ``','``         pixel marker\n",
      "    ``'o'``         circle marker\n",
      "    ``'v'``         triangle_down marker\n",
      "    ``'^'``         triangle_up marker\n",
      "    ``'<'``         triangle_left marker\n",
      "    ``'>'``         triangle_right marker\n",
      "    ``'1'``         tri_down marker\n",
      "    ``'2'``         tri_up marker\n",
      "    ``'3'``         tri_left marker\n",
      "    ``'4'``         tri_right marker\n",
      "    ``'8'``         octagon marker\n",
      "    ``'s'``         square marker\n",
      "    ``'p'``         pentagon marker\n",
      "    ``'P'``         plus (filled) marker\n",
      "    ``'*'``         star marker\n",
      "    ``'h'``         hexagon1 marker\n",
      "    ``'H'``         hexagon2 marker\n",
      "    ``'+'``         plus marker\n",
      "    ``'x'``         x marker\n",
      "    ``'X'``         x (filled) marker\n",
      "    ``'D'``         diamond marker\n",
      "    ``'d'``         thin_diamond marker\n",
      "    ``'|'``         vline marker\n",
      "    ``'_'``         hline marker\n",
      "    =============   ===============================\n",
      "    \n",
      "    **Line Styles**\n",
      "    \n",
      "    =============    ===============================\n",
      "    character        description\n",
      "    =============    ===============================\n",
      "    ``'-'``          solid line style\n",
      "    ``'--'``         dashed line style\n",
      "    ``'-.'``         dash-dot line style\n",
      "    ``':'``          dotted line style\n",
      "    =============    ===============================\n",
      "    \n",
      "    Example format strings::\n",
      "    \n",
      "        'b'    # blue markers with default shape\n",
      "        'or'   # red circles\n",
      "        '-g'   # green solid line\n",
      "        '--'   # dashed line with default color\n",
      "        '^k:'  # black triangle_up markers connected by a dotted line\n",
      "    \n",
      "    **Colors**\n",
      "    \n",
      "    The supported color abbreviations are the single letter codes\n",
      "    \n",
      "    =============    ===============================\n",
      "    character        color\n",
      "    =============    ===============================\n",
      "    ``'b'``          blue\n",
      "    ``'g'``          green\n",
      "    ``'r'``          red\n",
      "    ``'c'``          cyan\n",
      "    ``'m'``          magenta\n",
      "    ``'y'``          yellow\n",
      "    ``'k'``          black\n",
      "    ``'w'``          white\n",
      "    =============    ===============================\n",
      "    \n",
      "    and the ``'CN'`` colors that index into the default property cycle.\n",
      "    \n",
      "    If the color is the only part of the format string, you can\n",
      "    additionally use any  `matplotlib.colors` spec, e.g. full names\n",
      "    (``'green'``) or hex strings (``'#008000'``).\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(plt.plot)"
   ]
  },
  {
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       "0.007"
      ]
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    }
   ],
   "source": [
    "round(np.mean(Month_data['Return']), 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
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    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Return</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Day</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1995-03-31</th>\n",
       "      <td>-0.001466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-06-30</th>\n",
       "      <td>-0.025258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-09-30</th>\n",
       "      <td>0.145660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-12-31</th>\n",
       "      <td>-0.231358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996-03-31</th>\n",
       "      <td>0.001981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-30</th>\n",
       "      <td>-0.028603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>-0.043575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-03-31</th>\n",
       "      <td>0.022263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-30</th>\n",
       "      <td>-0.024255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-30</th>\n",
       "      <td>0.124383</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>119 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Return\n",
       "Day                 \n",
       "1995-03-31 -0.001466\n",
       "1995-06-30 -0.025258\n",
       "1995-09-30  0.145660\n",
       "1995-12-31 -0.231358\n",
       "1996-03-31  0.001981\n",
       "...              ...\n",
       "2023-09-30 -0.028603\n",
       "2023-12-31 -0.043575\n",
       "2024-03-31  0.022263\n",
       "2024-06-30 -0.024255\n",
       "2024-09-30  0.124383\n",
       "\n",
       "[119 rows x 1 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Quarter_data = data_new.resample('Q')['Return'].apply(lambda x: (1+x).prod()-1).to_frame()\n",
    "Quarter_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(Quarter_data['Return']) / len(Quarter_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    273.000000\n",
       "mean       0.005187\n",
       "std        0.071891\n",
       "min       -0.246314\n",
       "25%       -0.037082\n",
       "50%        0.004454\n",
       "75%        0.042370\n",
       "max        0.274464\n",
       "Name: Return, dtype: float64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Month_data['2002':\"2024\"]['Return'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
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      ]
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     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "len(data_new[data_new['Return'] > 0.1]) / len(data_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ]
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     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "len(Month_data[Month_data['Return'] > 0.1]) / len(Month_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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      ]
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     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(Quarter_data[Quarter_data['Return'] > 0.5]) / len(Quarter_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Variance</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Day</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
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       "      <th>1995-01-31</th>\n",
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       "    <tr>\n",
       "      <th>1995-02-28</th>\n",
       "      <td>0.001130</td>\n",
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       "    <tr>\n",
       "      <th>1995-03-31</th>\n",
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       "    <tr>\n",
       "      <th>1995-04-30</th>\n",
       "      <td>0.000407</td>\n",
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       "    <tr>\n",
       "      <th>1995-05-31</th>\n",
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       "      <th>2024-05-31</th>\n",
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       "      <th>2024-06-30</th>\n",
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       "      <th>2024-07-31</th>\n",
       "      <td>0.000065</td>\n",
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       "    <tr>\n",
       "      <th>2024-08-31</th>\n",
       "      <td>0.000031</td>\n",
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       "    <tr>\n",
       "      <th>2024-09-30</th>\n",
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       "            Variance\n",
       "Day                 \n",
       "1995-01-31  0.000260\n",
       "1995-02-28  0.001130\n",
       "1995-03-31  0.000551\n",
       "1995-04-30  0.000407\n",
       "1995-05-31  0.006924\n",
       "...              ...\n",
       "2024-05-31  0.000048\n",
       "2024-06-30  0.000031\n",
       "2024-07-31  0.000065\n",
       "2024-08-31  0.000031\n",
       "2024-09-30  0.000533\n",
       "\n",
       "[357 rows x 1 columns]"
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     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "Month_variance = data_new.resample('M')['Return'].var().to_frame()\n",
    "Month_variance.rename(columns={'Return':'Variance'}, inplace=True)\n",
    "Month_variance"
   ]
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   "cell_type": "code",
   "execution_count": 33,
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    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "ax.plot('Variance', \n",
    "        '^-',\n",
    "        label='Monthly Variance', \n",
    "        color='r',\n",
    "        linewidth=1,\n",
    "        data=Month_variance['2000':'2024'])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Variance</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Day</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
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       "      <th>1995-01-31</th>\n",
       "      <td>0.005695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-02-28</th>\n",
       "      <td>0.018086</td>\n",
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       "      <th>1995-03-31</th>\n",
       "      <td>0.013378</td>\n",
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       "    <tr>\n",
       "      <th>1995-04-30</th>\n",
       "      <td>0.008281</td>\n",
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       "    <tr>\n",
       "      <th>1995-05-31</th>\n",
       "      <td>0.148387</td>\n",
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       "      <td>...</td>\n",
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       "      <th>2024-05-31</th>\n",
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       "      <th>2024-06-30</th>\n",
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       "      <th>2024-07-31</th>\n",
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       "      <th>2024-08-31</th>\n",
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       "            Variance\n",
       "Day                 \n",
       "1995-01-31  0.005695\n",
       "1995-02-28  0.018086\n",
       "1995-03-31  0.013378\n",
       "1995-04-30  0.008281\n",
       "1995-05-31  0.148387\n",
       "...              ...\n",
       "2024-05-31  0.000915\n",
       "2024-06-30  0.000642\n",
       "2024-07-31  0.001441\n",
       "2024-08-31  0.000705\n",
       "2024-09-30  0.011045\n",
       "\n",
       "[357 rows x 1 columns]"
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     "execution_count": 35,
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   "source": [
    "Month_variance = data_new.resample('M')['Return'].apply(lambda x: sum(x**2)).to_frame()\n",
    "Month_variance.rename(columns={'Return':'Variance'}, inplace=True)\n",
    "Month_variance"
   ]
  },
  {
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   "execution_count": 36,
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   "source": [
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "ax.plot('Variance', \n",
    "        '^-',\n",
    "        label='Monthly Variance', \n",
    "        color='r',\n",
    "        linewidth=1,\n",
    "        data=Month_variance['2000':'2024'])\n",
    "\n",
    "plt.show()"
   ]
  }
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